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  1. A Quick Description Of Rate Distortion Theory.
  2.  
  3. We want to encode a video, picture or piece of music optimally. What does
  4. "optimally" really mean? It means that we want to get the best quality at a
  5. given filesize OR we want to get the smallest filesize at a given quality
  6. (in practice, these 2 goals are usually the same).
  7.  
  8. Solving this directly is not practical; trying all byte sequences 1
  9. megabyte in length and selecting the "best looking" sequence will yield
  10. 256^1000000 cases to try.
  11.  
  12. But first, a word about quality, which is also called distortion.
  13. Distortion can be quantified by almost any quality measurement one chooses.
  14. Commonly, the sum of squared differences is used but more complex methods
  15. that consider psychovisual effects can be used as well. It makes no
  16. difference in this discussion.
  17.  
  18.  
  19. First step: that rate distortion factor called lambda...
  20. Let's consider the problem of minimizing:
  21.  
  22.   distortion + lambda*rate
  23.  
  24. rate is the filesize
  25. distortion is the quality
  26. lambda is a fixed value chosen as a tradeoff between quality and filesize
  27. Is this equivalent to finding the best quality for a given max
  28. filesize? The answer is yes. For each filesize limit there is some lambda
  29. factor for which minimizing above will get you the best quality (using your
  30. chosen quality measurement) at the desired (or lower) filesize.
  31.  
  32.  
  33. Second step: splitting the problem.
  34. Directly splitting the problem of finding the best quality at a given
  35. filesize is hard because we do not know how many bits from the total
  36. filesize should be allocated to each of the subproblems. But the formula
  37. from above:
  38.  
  39.   distortion + lambda*rate
  40.  
  41. can be trivially split. Consider:
  42.  
  43.   (distortion0 + distortion1) + lambda*(rate0 + rate1)
  44.  
  45. This creates a problem made of 2 independent subproblems. The subproblems
  46. might be 2 16x16 macroblocks in a frame of 32x16 size. To minimize:
  47.  
  48.   (distortion0 + distortion1) + lambda*(rate0 + rate1)
  49.  
  50. we just have to minimize:
  51.  
  52.   distortion0 + lambda*rate0
  53.  
  54. and
  55.  
  56.   distortion1 + lambda*rate1
  57.  
  58. I.e, the 2 problems can be solved independently.
  59.  
  60. Author: Michael Niedermayer
  61. Copyright: LGPL
  62.